Evidence map›Paper›PMID 28751838›Full record

ArticleEuropean heart journal supplements : journal of the European Society of Cardiology2017

ANMCO/ELAS/SIBioC Consensus Document: biomarkers in heart failure.

Nadia Aspromonte, Michele Massimo Gulizia, Aldo Clerico, Giuseppe Di Tano, Michele Emdin, Mauro Feola, Massimo Iacoviello, Roberto Latini, Andrea Mortara, Roberto Valle and 6 more

Abstract read
In one paragraph

Article in European heart journal supplements : journal of the European Society of Cardiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Review
  3. The Liver in Heart Failure: From Biomarkers to Clinical Risk.International journal of molecular sciences · 2023
    Review
  4. Neurohumoral Activation in Heart Failure.International journal of molecular sciences · 2023
    Review
  5. Review
  6. Review
  7. Galectin-3 in Cardiovascular Diseases.International journal of molecular sciences · 2020
    Review
  8. miR-129-5p improves cardiac function in rats with chronic heart failure through targeting HMGB1.Mammalian genome : official journal of the International Mammalian Genome Society · 2019
    Article
  9. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Nadia AspromonteCCU-Cardiology Department, Presidio Ospedaliero San Filippo Neri, Via Martinotti, 20, 00135 Rome, Italy.
Michele Massimo GuliziaCardiology Department, Ospedale Garibaldi-Nesima, Azienda di Rilievo Nazionale e Alta Specializzazione "Garibaldi", Catania, Italy.
Aldo ClericoLaboratory of Endocrinology and Cardiovascular Cell Biology, Fondazione Toscana G. Monasterio-CNR, Scuola Superiore Sant'Anna, Pisa, Italy.
Giuseppe Di TanoIstituti Ospitalieri, Cardiology Unit, Cremona, and Scuola Superiore Sant'Anna, Pisa, Italy.
Michele EmdinCardiology and Cardiovascular Medicine Department, Fondazione Toscana G. Monasterio, Italy.
Mauro FeolaCardiac Rehabilitation - Congestive Cardiac Unit, Ospedale Maggiore SS. Trinità, Fossano (CN), Italy.
Massimo IacovielloCardiology University Unit, Ospedale Policlinico, Bari, Italy.
Roberto LatiniCardiovascular Research Department, Istituto Mario Negri, Milano, Italy.
Andrea MortaraClinical Cardiology and Heart Failure Unit, Policlinico di Monza, Monza (MB), Italy.
Roberto ValleCardiology Department, Ospedale Civile, Chioggia (Venezia), Italy.
Gianfranco MisuracaCardiology Department, Ospedale SS. Annunziata, Cosenza, Italy.
Claudio PassinoCardiology and Cardiovascular Medicine Department, Fondazione Toscana G. Monasterio, Italy.
Serge MassonCardiovascular Research Department, Istituto Mario Negri, Milano, Italy.
Alberto AimoCardiology and Cardiovascular Medicine Department, Fondazione Toscana G. Monasterio, Italy.
Marcello CiaccioClinical Biochemistry and Molecular Medicine Section, Dipartimento di Pathobiology and Medical Biotechnology Department, Università degli Studi, Palermo, Italy.
Marco MigliardiLaboratory of Analysis, A.O. Ordine Mauriziano, Torino, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biomarkers have dramatically impacted the way heart failure (HF) patients are evaluated and managed. A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biological or pathogenic processes, or pharmacological responses to a therapeutic intervention. Natriuretic peptides [B-type natriuretic peptide (BNP) and N-terminal proBNP] are the gold standard biomarkers in determining the diagnosis and prognosis of HF, and a natriuretic peptide-guided HF management looks promising. In the last few years, an array of additional biomarkers has emerged, each reflecting different pathophysiological processes in the development and progression of HF: myocardial insult, inflammation, fibrosis, and remodelling, but their role in the clinical care of the patient is still partially defined and more studies are needed before to be well validated. Moreover, several new biomarkers have the potential to identify patients with early renal dysfunction and appear to have promise to help the management cardio-renal syndrome. With different biomarkers reflecting HF presence, the various pathways involved in its progression, as well as identifying unique treatment options for HF management, a closer cardiologist-laboratory link, with a multi-biomarker approach to the HF patient, is not far ahead, allowing the unique opportunity for specifically tailoring care to the individual pathological phenotype.

Indexed as

BiomarkersFibrosisGalectin 3Heart failureInflammationNatriuretic peptidesTroponin

Identifiers

PMID28751838
PMCPMC5520761

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.